Descriptive Statistics

Analysis of Averages I have calculated the mean of all the Spotify Audio feature’s for each of the playlist’s in my corpus. This will allow my to find the most typical and atypical tracks.

Danceability Danceability seems to be higher in the playlists from the West Coast, highlighting the liveliness and positive mood of West Coast hip-hop music.

All the means are quite close to each other but the Southern playlist leans towards the West Coast in terms of danceability.

Valence Valence is higher for the “classic” playlists, this trend is clear with the West Coast, East Coast and Southern Classic playlists. Songs during the classical period of Hip-Hop tended to be a lot more optimistic. Today rap is a lot more depressing.

Energy Energy is highest in the Southern Classics playlist, this makes sense to me due to the very distinct production present in Southern American hip-hop.

Acousticness Surprisingly enough acousticness seems to be stronger in the modern playlists. The weak nature or lack of acousticness in the old school playlists could be due to the novel presence of electronic music during the era of old school hip-hop. Tracks contained a lot more electric instruments such as electric synthesizers, guitars and drums. Modern hip-hop tends to be more acoustic with more use of instruments and human vocals.

Speechiness

Tempo

Instrumentalness

Liveness

Visualising the guesses

These charts display four important metrics for each playlist in my corpus. We compare valence, energy, loudness and mode in this comprehensive visualization.

need to fix the legend

Most average songs

get_most_average_song <- function(playlist) 
{
  metrics<-c("danceability","energy","key","loudness","mode","speechiness",
             "acousticness","instrumentalness","liveness","valence","tempo")
  
  mean_metrics=colMeans(playlist[,metrics])
  playlist$diff=rep(0,nrow(playlist))
  
 for(i in 1:nrow(playlist)) {
  playlist[i,'diff']<-sum(abs(playlist[i,metrics]-mean_metrics[metrics]))
 }
  song=playlist$track.name[which.min(playlist$diff)]
  return (list(playlist,song))
}

east<-get_most_average_song(east)[[1]]
east_song_name<-get_most_average_song(east)[[2]]

west<-get_most_average_song(west)[[1]]
west_song_name<-get_most_average_song(west)[[2]]

east_new<-get_most_average_song(east_new)[[1]]
east_new_song_name<-get_most_average_song(east_new)[[2]]

west_new<-get_most_average_song(west_new)[[1]]
west_new_song_name<-get_most_average_song(west_new)[[2]]

The most average song from I love My West Coast Classics is Fuck Tha Police.

The most average song from I Love My East Coast Classics is Loungin (Who Do Ya Luv) - Remix.

The most average song from Cali Fire is Paranoia / #1 Stunna.

The most average song from State of Mind is Proud Of Me Now.

The function calculates the sum of absolute distances between each feature of the songs in the playlist and the feature’s mean. The songs with the minimum difference are chosen to be the ‘most average’.

Pitch Analysis Classics

The first thing to point out is that Loungin is a lot shorter. As for the pitch: in Loungin higher pitches are more prevalent and in Fuck Tha Police there’s more lower pitches.

Pitch Analysis Modern

Again, the East coast song is shorter and middle pitches are more prevalent. The west coast song has a lot of low pitches.

Chord and Key Comparison of two old school hip-hop songs

Fuck Tha Police

Loungin (Who Do Ya Luv) - Remix

The Chords look fairly similar between coasts. The keys are very different. The East coast song is mainly in minor keys, except for one moment around 90 seconds. The West coast song has more diversity in keys.

Chord and Key Comparison Modern

Paranoia / #1 Stunna

Proud Of Me Now

The Modern songs are more different between coasts.The West coast song has two periods where there’s more intensity in both Chords and Keys, while for the East coast song things only happen in the very beginning.

Tempo Novelty

Classics

Modern

These plots potentially suggest a great feature to differentiate between the old and new songs-tempo novelty in the beginning of the song. Both old songs start with a big drop, while the new songs do not have it. Also, East coast songs seem to change tempo more frequently compared to the West ones.

Classification

# A tibble: 4 x 3
  class               precision recall
  <fct>                   <dbl>  <dbl>
1 East Coast Classics     0.579   0.55
2 East Coast Modern       0.5     0.35
3 West Coast Classics     0.682   0.75
4 West Coast Modern       0.560   0.7 

Here a random forest is estimated. It is interesting that precision is higher for some playlist than for others. This suggests that West Coast Classics is the most different from the rest of the playlists (easiest to classify correctly). The feature importance graph shows that duration, tempo, valence and acousticness are important in differentiating among playlists. This, on the one hand, is helpful in playlist comparison, but also to suggest which features are the most important to look at when aiming to classify new songs. It is worth noting that the sample is very small - only 20 songs for each playlist and that they are selected not randomly, but the first 20, which introduces a bias of Spotify selection.